Vehicle propulsion system having an energy storage system and optimized method of controlling operation thereof

ABSTRACT

A charging system for a vehicle includes a first energy storage device, a first DC-DC converter coupled between a DC bus and the first energy storage device, and a controller. The controller is programmed to identify charging parameters of a charging source coupleable to the first energy storage device through the first DC-DC converter, apply an optimization algorithm to iteratively define a charging power allocation to charge the first energy storage device using the charging source, and selectively control the first DC-DC converter to recharge the first energy storage device in accordance with the charging power allocation. The charging power allocation optimizes at least one of a state of charge (SOC) and a state of health (SOH) of the first energy storage device.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation-in-part of, and claimspriority to, U.S. non-provisional application Ser. No. 14/462,765, filedAug. 19, 2014, and U.S. non-provisional application Ser. No. 14/462,792,filed Aug. 19, 2014, the disclosures of which are incorporated herein byreference in their entirety.

BACKGROUND OF THE INVENTION

Embodiments of the invention relate generally to electric drive systemsfor hybrid and electric vehicles and, more particularly, to a vehiclepropulsion system for hybrid and electric vehicles with one or moreenergy storage devices and one or more electromechanical devices and anoptimized method of controlling operation of the vehicle propulsionsystem.

Purely electric vehicles use stored electrical energy to power anelectric motor, which propels the vehicle and may also operate auxiliarydrives. Purely electric vehicles may use one or more sources of storedelectrical energy. For example, a first source of stored electricalenergy may be used to provide longer-lasting energy while a secondsource of stored electrical energy may be used to provide higher-powerenergy for, for example, acceleration, with one or both the first andsecond sources being capable of being charged through regenerativebraking.

Hybrid electric vehicles may combine an internal combustion engine andan electric motor powered by an energy storage device, such as atraction battery, to propel the vehicle. Such a combination may increaseoverall fuel efficiency by enabling the combustion engine and theelectric motor to each operate in respective ranges of increasedefficiency. Electric motors, for example, may be efficient ataccelerating from a standing start, while combustion engines may beefficient during sustained periods of constant engine operation, such asin highway driving. Having an electric motor to boost initialacceleration allows combustion engines in hybrid vehicles to be smallerand more fuel efficient.

While propulsion system configurations for purely electric vehicles andhybrid electric vehicles have been developed to include multiple sourcesof electrical energy to increase energy or power density and multiplepower sources to achieve desired propulsive output, incorporating theseenergy storage and power sources into a propulsion system increases theoverall size, weight, and cost of the system. For example, to ensure aminimum level of performance will be maintained over the desired life ofthe vehicle, batteries are often oversized to reduce power and cyclicstresses. Also, overly aggressive thermal management controls areimplemented to help reduce thermal stresses on the batteries. Both ofthese approaches increase the overall vehicle size, increasemanufacturing costs, and increase the operating costs of the energystorage system.

Traditional energy storage units for hybrid and electric vehicles aredesigned and implemented with little control over the degradation rateof the energy storage units or batteries within the system. Knownbattery life prognosis is performed off-line using physics-based modelsto predict the rate of various individual degradation mechanisms. Theseexperimental models may take into account solid-electrolyte interphase(SEI) resistance growth and capacity fade, chemical reaction paths forSEI growth, the onset of particle fracture due to high-ratecharge/discharge, or the electrochemical state for a single duty-cycleof a battery. To date, however, known models do not predict thepost-initiation crack propagation needed to correlate actual capacityfade with the experimental data and lack the predictive capability forarbitrary battery duty-cycles.

Further, the off-line life testing of battery technologies is typicallyperformed in an accelerated manner that condenses many cycles into amuch shorter period of time than the battery would experience duringnormal operation. As such, the empirical models developed usingaccelerated aging testing may not accurately account for theinteractions between the calendar-related and cycling-related responseof the battery in a real-time, real-world application.

In addition to the operation of energy storage units, the systemefficiency of hybrid and electric power systems is also affected by theDC link voltage of the drive system. One known technique for determiningthe DC link voltage uses a comprehensive model to calculate a DC busvoltage that minimizes motor and inverter loss for a particular vehiclepropulsion system configuration. Use of such a comprehensive model istime intensive and results in expensive hardware deployment. Moreover,such a method relies on the model's accuracy and is inevitably notrobust to varying system components and operational modes. Anothertechnique for determining a DC link voltage uses a motor systemefficiency map to search for a voltage level with minimal loss. As thistechnique relies on a direct look-up table, noise on all input appearson the output voltage command. Moreover, the look-up table is static anddoes not take system dynamics into account. Thus, a sudden load changemay cause unsatisfactory responsive performance on motor torque due tothe latency of the voltage command. The comprehensive model likewisefails to respond satisfactorily to sudden load changes, typically addinga predetermined margin to the voltage command to accommodate any dynamicuncertainly. However, such a predetermined margin often produces anunsatisfactory response; since too large of a margin sacrifices systemefficiency while too small of a margin will not meet the requesteddynamic response.

As outlined above, known techniques for configuring a hybrid or electricpropulsion system to operate with multiple energy storage sources andone or more power sources rely on experimentally determined models andstatic data that does not account for real-time, real-world systemdynamics and operating conditions. Accordingly, use of these knowntechniques reduces the operating efficiency and fuel economy of theindividual components of the propulsion system in addition to reducingthe overall system efficiency.

Therefore, it would be desirable to provide an electric and/or hybridelectric propulsion system that improves overall system efficiency andoptimizes the operation and lifespan of the energy storage units andoperating efficiency, while permitting the propulsion system to bemanufactured at a reduced cost.

BRIEF DESCRIPTION OF THE INVENTION

According to one aspect of the invention, a charging system for avehicle includes a first energy storage device, a first DC-DC convertercoupled between a DC bus and the first energy storage device, and acontroller. The controller is programmed to identify charging parametersof a charging source coupleable to the first energy storage devicethrough the first DC-DC converter, apply an optimization algorithm toiteratively define a charging power allocation to charge the firstenergy storage device using the charging source, and selectively controlthe first DC-DC converter to recharge the first energy storage device inaccordance with the charging power allocation. The charging powerallocation optimizes at least one of a state of charge (SOC) and a stateof health (SOH) of the first energy storage device.

In accordance with another aspect of the invention, a method of chargingan energy storage system of a vehicle includes identifying operatingparameters a plurality of energy storage units of the energy storagesystem, identifying a charging source available to recharge theplurality of energy storage units, and defining a charging powerallocation to recharge the plurality of energy storage units using thecharging source. The method also includes iteratively adjusting thecharging power allocation to optimize at least one of a state of healthand a state of charge of the plurality of energy storage units, andrecharging at least one energy storage unit of the energy storage systemin accordance with the adjusted charging power allocation.

In accordance with yet another aspect of the invention, a vehiclepropulsion system includes a first energy storage unit coupled to a DCbus via a DC-DC converter, a switching device operable to couple acharging source to the DC bus, and a controller electrically coupled tothe switching device and the DC-DC converter. The controller isprogrammed to query parameters of a charging power available from thecharging source, access a state of charge (SOC) of the first energystorage unit and define a charging power allocation to recharge thefirst energy storage device with the charging power. The controller isfurther programmed to apply a multi-objective optimization algorithm toiteratively adjust the charging power allocation based on the parametersof the charging power and the SOC of the first energy storage unit andrecharge the first energy storage unit in accordance with the adjustedcharging power allocation.

Various other features and advantages will be made apparent from thefollowing detailed description and the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings illustrate embodiments presently contemplated for carryingout the invention.

In the drawings:

FIG. 1 is a schematic diagram of a vehicle propulsion system accordingto an embodiment of the invention.

FIG. 2 is a schematic diagram of a vehicle propulsion system accordingto another embodiment of the invention.

FIG. 3 is a schematic diagram of a vehicle propulsion system accordingto another embodiment of the invention.

FIG. 4 is a schematic diagram of a simulation model for generating adesign configuration of an energy storage system according to anembodiment of the invention.

FIG. 5 illustrates a dynamic control technique for splitting a totalpower demand of a vehicle propulsion system between a plurality ofenergy storage units according to an embodiment of the invention.

FIG. 6 illustrates a dynamic control technique for regulating a DC busvoltage a vehicle propulsion system according to an embodiment of theinvention.

FIG. 7 is an exemplary voltage scheduling map for use with the dynamiccontrol technique of FIG. 6.

FIG. 8 illustrates a dynamic control technique for splitting a totalpower demand of a vehicle propulsion system between a plurality of powersources of a powertrain according to an embodiment of the invention.

FIG. 9 is a schematic diagram of a vehicle propulsion system accordingto another embodiment of the invention.

FIG. 10 illustrates a dynamic control technique for recharging one ormore energy storage units using available charging power according to anembodiment of the invention.

DETAILED DESCRIPTION

FIG. 1 is a schematic diagram of a propulsion system 10 according to anembodiment of the invention. As described in detail below, propulsionsystem 10 may be configured in a pure electric (EV) propulsion systemarrangement that splits power output between one or moreelectromechanical devices or as a hybrid (HEV) propulsion system thatincludes an internal combustion engine in addition to one or moreelectromechanical devices. In either an EV or HEV embodiment, theelectromechanical devices are provided on a common DC bus or on anoutput port of independent channels of a multi-channel DC-DC converter,simplifying the electrical DC bus and cabling structure and saving costwhile still permitting flexibility in the sizing and operation of themultiple electromechanical devices and increasing the operatingefficiency of the electromechanical devices and overall propulsionsystem.

According to various embodiments, propulsion system 10 is configured tobe incorporated into various types of vehicles including, but notlimited to, automobiles, busses, trucks, tractors, commercial andindustrial vehicles such as mining and construction equipment, marinecraft, aircrafts and off-road vehicles, including material transportvehicles or personal carrier vehicles, capable of operation both on thesurface and underground such as in mining operations, or other type ofelectrical apparatus such as, for example, a crane, elevator, or lift,as non-limiting examples.

Propulsion system 10 includes an energy storage system 12 having a firstenergy storage unit 14 and a second energy storage unit 16. Each energystorage unit 14, 16 have a positive terminal 18, 20 and a negativeterminal 22, 24. Positive terminal 18 of first energy storage unit 14 iscoupled to a first bi-directional DC-DC converter 26 and positiveterminal 20 of second energy storage unit 16 is coupled to a secondbi-directional DC-DC converter 28. Each of the first and second energystorage units 14, 16 has a separate or integrated energy storagemanagement system (not shown), which may be configured as a batterymanagement system (BMS) in an embodiment the respective energy storageunit is a battery. According to another embodiment, bi-directional DC-DCconverters 26, 28 are bi-directional DC-DC voltage converters orbi-directional buck/boost voltage converters.

A sensor system 30 is provided within propulsion system 10 to monitorand calculate the state-of-charge (SOC) of the first and second energystorage units 14, 16. According to one embodiment, sensor system 30includes voltage sensors and/or current sensors configured to measurethe voltage and/or current of first and second energy storage units 14,16 at various times during operation thereof.

According to various embodiments, first and second energy storage units14, 16 each include one or more energy storage devices such as abattery, a flywheel, fuel cell, an ultracapacitor, or a combination ofultracapacitors, fuel cells, and/or batteries, as examples. In oneembodiment, first energy storage unit 14 is a high specific-power energystorage device and second energy storage unit 16 is a highspecific-energy storage device. For example, first energy storage unit14 may be an ultracapacitor having multiple capacitor cells coupled toone another, where the capacitor cells may each have a capacitance thatis greater than approximately 500 Farads. Alternatively, first energystorage unit 14 may be a high power battery having a specific-power ofapproximately 350 W/kg or greater or a combination of one or moreultracapacitors and batteries. In such an embodiment, second energystorage unit 16 has a relatively low specific power as compared withfirst energy storage unit 14. As used herein, low specific powerdescribes an energy storage device demonstrated to achieve a specificpower on the order of approximately 200 W/kg or lower. According tovarious embodiments, second energy storage unit 16 may be, for example,a high specific energy battery or high energy density battery. The termenergy battery used herein describes a high specific energy batterydemonstrated to achieve a specific energy on the order of 100 W-hr/kg orgreater (e.g., a Li-ion, sodium-metal halide, sodium nickel chloride,sodium-sulfur, Li-Air, or zinc-air battery).

In one embodiment, second energy storage unit 16 has a relatively highresistivity and impedance as compared with first energy storage unit 14.In another embodiment, the relatively low specific power of secondenergy storage unit 16 may be due to an imbalance of the individualbattery cells comprising the energy storage system. In one embodiment,second energy storage unit 16 is a low-cost lithium ion battery.Alternatively, second energy storage unit 16 may be a sodium metalhalide battery, a sodium sulfur battery, a nickel metal hydride battery,a Zinc-air battery, a lead acid battery, and the like.

Propulsion system 10 also includes a first bi-directional DC-DCconverter 26 and second bi-directional DC-DC converter 28 are coupledacross the positive DC link 32 and the negative DC link 34 of a DC bus36. A voltage sensor 38 is coupled across DC bus 36 to monitor a DC busvoltage. In another embodiment, sensor 38 is embedded in one of theDC-DC converters.

According to one embodiment, either or both of first and second energystorage units 14, 16 may be sized such that the respectivebi-directional DC-DC converters 26, 28 may be omitted, resulting in apropulsion system 10 that includes fewer parts and less weight than asystem that includes a respective DC-DC voltage converter for eachenergy storage system. In such an embodiment, a contactor (not shown)may be provided to selectively couple the respective energy storage unitto the DC bus.

Both first bi-directional DC-DC converter 26 and second bi-directionalDC-DC converter 28, when used, are configured to convert one DC voltageto another DC voltage either by bucking or boosting the DC voltage.According to one embodiment, each bi-directional DC-DC converter 26, 28includes an inductor coupled to a pair of electronic switches andcoupled to a pair of diodes. Each switch is coupled to a respectivediode, and each switch/diode pair forms a respective half phase module.Switches may be, for example, insulated gate bipolar transistors(IGBTs), metal oxide semiconductor field effect transistors (MOSFETs),silicon carbide (SiC) MOSFETs, Gallium nitride (GaN) devices, bipolarjunction transistors (BJTs), and metal oxide semiconductor controlledthyristors (MCTs).

First and second energy storage units 14, 16 are coupled via DC bus 36to a first load 40 and an optional second load 42 (shown in phantom). Inone embodiment, first and second loads 40, 42 are electric drives. Firstload 40 includes a first DC-to-AC voltage inverter 44 and a first motoror first electromechanical device 46. Second load 42 includes a secondDC-to-AC voltage inverter 48 and a second motor or secondelectromechanical device 50. In one embodiment, each inverter 44, 48includes six half phase modules that are paired to form three phases,with each phase is coupled between the positive and negative DC links32, 34 of the DC bus 36.

Each electromechanical device 46, 50 includes a plurality of windingscoupled to respective phases of its respective DC-to-AC voltage inverter44, 48. In one embodiment, electromechanical device 46 is a tractionmotor and electromechanical device 50 is either an alternator or afraction motor. In another embodiment, electromechanical devices 46, 50are AC motors. Sensor assemblies, generally indicated as part numbers 52and 54 in FIG. 1, include various current and/or voltage sensors tomonitor torque and speed of the respective electromechanical devices 46,50.

Although the propulsion system 10 is described herein as includingthree-phase inverters 44, 48 and three-phase electromechanical devices46, 50, it is contemplated that propulsion system 10 may utilize anynumber of phases in alternative embodiments.

Propulsion system 10 also includes a transmission 56 coupled to theoutputs of first and second electromechanical devices 46, 50.Transmission 56 is constructed as a gear assembly, belt assembly, orcombination thereof according to various embodiments. According to oneembodiment, transmission 56 is configured as an electrically variabletransmission (EVT) that couples the outputs of electromechanical devices46, 50 through an arrangement of internal planetary gears and clutches(not shown). In operation, electromechanical devices 46, 50 may beoperated over a wide range of bi-directional speed, torque, and powercommands to minimize power loss and maintain a high degree of overallsystem efficiency while propulsion system 10 is operating in either acharge depleting (CD) or charge sustaining (CS) mode of operation.

The output of transmission 56 is coupled to one or more driving wheels58 or axles of a vehicle through a gear assembly 60, which may include adifferential. Depending on how the clutches of transmission 56 areconfigured, first or second electromechanical device 46, 50 may becoupled to gear assembly 60 through transmission 56 or may be directlycoupled to gear assembly 60 such that the output of first or secondelectromechanical device 46, 50 bypasses transmission 56.

According to one embodiment propulsion system 10 is configured as a pureelectric vehicle (EV) propulsion system. Alternatively, propulsionsystem 10 is configured in a hybrid electric vehicle (HEV) propulsionsystem and also includes an internal combustion engine (ICE) 62 (shownin phantom) coupled to transmission 56. According to variousembodiments, internal combustion engine 62 may be an internal combustiongasoline engine, an internal combustion diesel engine, an internalcombustion engine fueled by natural gas, an external combustion engine,or a gas turbine engine, as non-limiting examples.

Propulsion system 10 also includes a controller 64 operably coupled tofirst and second bi-directional DC-DC converters 26, 28 by control lines66. Through appropriate control of the switches of first bi-directionalDC-DC converter 26, controller 64 is configured to boost a voltage offirst energy storage unit 14 to a higher voltage and to supply thehigher voltage to the DC bus 36. Likewise, controller 64 is configuredto control switching of second bi-directional DC-DC voltage converter 28to boost the voltage of energy storage unit 16 to a higher voltage andto supply the higher voltage to the DC bus 36 during a motoring mode ofoperation. Controller 64 is also configured to control switching offirst and second bi-directional DC-DC converters 26, 28 to buck avoltage of DC bus 36 and to supply the bucked voltage to the respectivefirst or second energy storage unit 14, 16 during a charging orregenerative mode of operation. In one embodiment control lines 66include a real or virtual communication data link that conveys thevoltage commands to the respective bi-directional DC-DC converter 26,28.

Controller 64 is also coupled to first DC-to-AC voltage inverter 44 andsecond DC-to-AC voltage inverter 48 through control lines 68. In amotoring mode, controller 64 is configured to control the half phasemodules of first and second DC-to-AC voltage inverters 44, 48 to convertthe DC voltage or current on DC bus 36 to an AC voltage or current forsupply to the electromechanical devices 46, 50. When accelerating in themotoring mode, propulsion system 10 increases the speed of rotation ofone or both of electromechanical devices 46, 50 from zero or from itsreal-time or current speed to a higher speed. In a regenerative mode,controller 64 is configured to control first and second DC-to-AC voltageinverters 44, 48 to invert an AC voltage or current received from itscorresponding electromechanical device 46, 50 into a DC voltage orcurrent to supply to DC bus 36.

During operation controller 64 also receives feedback from voltagesensor 38 via control lines 70 and from energy storage unit sensorsystem 30 via control lines 72. As one skilled in the art willrecognize, additional voltage and/or current sensors may be providedthroughout propulsion system 10 to permit controller 64 to monitor otheroperating conditions. In addition, one skilled in the art will recognizethat controller 64 may receive feedback from and/or transmit controlcommands to other components within propulsion system 10, such as, forexample, internal combustion engine 62.

While the energy storage system 12 of propulsion system 10 is describedherein as including two energy storage units, it is contemplated thatalternative embodiments may include a single energy storage unit coupledto a single DC-DC voltage converter assembly or three or more energystorage units either directly coupled to DC bus 36 or coupled to DC bus36 via one of first and second bi-directional DC-DC converter 26, 28 oran additional DC-DC converter. In addition, alternative embodiments mayinclude a single electromechanical device/DC-to-AC voltage inverter paircoupled to DC bus 36 or three or more electromechanical devices coupledto DC bus 36 via respective DC-to-AC voltage inverters.

According to one embodiment, propulsion system 10 includes a database 74configured to store information related to the propulsion system 10.Such information may include, as examples, degradation models for energystorage units 14, 16, predefined voltage scheduling maps for theelectromechanical devices 46, 50, and historical or known accelerationand deceleration periods of the vehicle along a known route or accordingto vehicle acceleration/deceleration trends or a predefined duty cycle.An optional vehicle position sensor 76 (shown in phantom) may beprovided to determine a position of the vehicle along a route based onposition identifiers such as mile markers, time of day, or globalpositioning system (GPS) location information, for example, with thevehicle position information being related to acceleration anddeceleration events stored in database 74. Each acceleration anddeceleration event in database 74 may also contain information regardingthe time duration of an acceleration or deceleration event.

Referring now to FIG. 2, a propulsion system 78 is illustrated accordingto an alternative embodiment. Similar to propulsion system 10,propulsion system 78 includes first and second electromechanical devices46, 50 coupled to respective first and second DC-to-AC voltage inverters44, 48. Other elements and components common to propulsion system 10 andpropulsion system 78 are referred to herein with similar part numberingas appropriate.

As shown in FIG. 2, first DC-to-AC voltage inverter 44 is coupled tofirst energy storage unit 14 through a first DC bus 80 having a positiveDC link 82 and a negative DC link 84. Likewise, second DC-to-AC voltageinverter 48 is coupled to second energy storage unit 16 through positiveDC link 86 and negative DC link 88 of a second DC bus 90. Optionally,first and second bi-directional DC-DC converters 26, 28 (shown inphantom) may be coupled between energy storage units 14, 16 and DC-to-ACvoltage inverters 44, 48 and operated via controller 64 to selectivelyboost the voltage of respective energy storage units 12, 16 to the busvoltage of the corresponding first or second DC bus 80, 90 during amotoring mode and buck the voltage of first or second DC bus 80, 90 to avoltage of respective energy storage unit 12, 16 during a regenerativeor recharging mode.

In embodiments where either or both of the DC-DC converters 26, 28 areomitted from propulsion system 78, the overall system architecture issimplified and the weight and volume of the propulsion system 78 isreduced. However, the omission of these components from the systemtopology may result in lower efficiency and less flexibility of controlsand optimization as a result of the loss of control of the voltage ofthe first and second DC buses 80, 90.

Because propulsion system 78 is configured with two independent DCbusses 80, 90, the DC link voltage of each bus 80, 90 may beindependently selected and controlled. In addition, the independent DClink voltages provides for greater flexibility in selecting and sizingthe energy storage units 14, 16 and electromechanical devices 46, 50 formaximum system efficiency.

FIG. 3 is a schematic diagram of a propulsion system 92 according toanother embodiment of the invention. Elements and components common topropulsion systems 10, 78, and 92 are referred to relative to the samereference numbers as appropriate. Propulsion system 92 differs frompropulsion systems 10, 78 in that first and second integrated powerelectronics assemblies 94, 96 replace the DC-DC voltage converterassemblies and DC-AC inverters of propulsion systems 10 and 78 (FIGS. 1and 2). Each integrated power electronics assembly 94, 96 of FIG. 3includes a DC-DC voltage converter and an DC-AC inverter combined withina common hardware packaging. Such an embodiment provides for moreeffective thermal management of the power electronics and a more compactdesign. However, repair costs for propulsion system 92 may be higherthan those for propulsion systems 10, 78 because the voltage converterand inverter electronics are packaged in the same housing, the entirepackaging assembly may need to be replaced when one component fails.

The design configuration of the energy storage system 12 of FIGS. 1, 2,and 3 is determined using an energy storage system simulation module 98schematically illustrated in FIG. 4. As described in detail below,simulation module 98 is operated offline and uses a collection of energystorage unit models, operational data, and economic data to define aconfiguration for an energy storage system that is capable of providingdesired performance characteristics for propulsion system operation andthat also minimizes the cost and sizing of the individual energy storageunits within the energy storage system.

Simulation module 98 receives as an input operational use data 100 thatincludes data for a broad range of possible usage patterns for theindividual energy storage units that may be included within energystorage system 12. Such operational use data 100 may include, forexample, a selection of predetermined or standard duty or drive cycles,such as a city drive cycle and a highway drive cycle, which includedetails on how the power demand over the exemplary drive cycle varies.Simulation module 98 also receives economic scenario data 102 thatincludes parameters that account for variations in the initial capitalcosts of various types of energy storage units and vehicle operationscosts including, for example, operating costs for vehicles incorporatingdifferent types of energy storage units and/or costs to rechargedifferent types of energy storage units.

Provided within energy storage system simulation module 98 arephysics-based models 104, such as, for example, electrochemical models,for various types of energy storage units that may be included withinthe energy storage system 12. Simulation module 98 also includesdegradation models 106 of various types of energy storage units.

An optimization algorithm 108 is applied to the simulation module 98 todetermine an optimized configuration for energy storage system 12,taking into account the physics-based models 104 and degradation models106 of the various options for energy storage units, the operation usedata 100, and economic scenario data 102 for the propulsion system.

The resulting output 110 of the simulation module 98 is a design forenergy storage system 12 that includes a selection of the type of energystorage units within energy storage system 12, such as power batteriesand/or energy batteries for example, and an optimized sizing of thoseenergy storage units, which may include the power of each energy storageunit defined in kilowatts as well as the energy of each energy storageunit defined in kilowatt-hours. As one non-liming example, the output110 of simulation module 98 may define an energy storage system 12 asincluding a 10 kW, 20 kW-hr power battery and a 10 kW, 50 kW-hr energybattery.

The energy storage system design output by simulation module 98 may besuitable for most, if not all, operational use and economic scenarios ofthe propulsion system. For example, a particular design could be statedto achieve 10 years of life for 85% of the customers, whereas anotherdesign option may achieve nine years of life for 95% of the customers.

In addition to providing an optimized design configuration for energystorage system 12 through the offline use of simulation module 98,embodiments of the invention also provide online optimization of energystorage system 12 through the operation of a dynamic power-split controltechnique 112 illustrated in FIG. 5, during which controller 64selectively draws power from energy storage units 14, 16 according to acontrol strategy designed to optimize the power split among the energystorage units 14, 16 while maximizing the overall operating efficiencyof propulsion system 10. The power-split control technique 112 isoperated in real-time and effects a split of the total power demand forthe propulsion system 10 between the energy storage units 14, 16 whileconsidering a broad range of possible usage patterns for the energystorage units, degradation models for the energy storage units,awareness of possible future demands, and a power dispatch algorithm.While dynamic control technique 112 is described below with reference topropulsion system 10 of FIG. 1, it will be appreciated that technique112 may readily to be extended to propulsion systems having alternativeconfigurations, such as, for example, propulsion system 78 (FIG. 2) andpropulsion system 92 (FIG. 3).

Dynamic power-split control technique 112 begins at step 114 byaccessing an initial power split for the energy storage units 14, 16,which defines how the total power demand of the propulsion system 10 isto be divided between the energy storage units 14, 16 for a givenoperating period. At vehicle startup, the initial power split may bedefined as a default value determined from a preset duty or drive cyclefor propulsion system 10. In operation, the initial power split may bedefined as the most recent power split applied to the energy storageunits 14, 16.

At step 116, operating parameters for the first and second energystorage units 14, 16 are monitored. In one embodiment, the operatingparameters include a real-time value of the state-of-charge (SOC) of theenergy storage units 14, 16 and a real-time value state-of-health (SOH)of the energy storage units 14, 16. These real-time SOC and SOH values116 may be determined from information received from energy storage unitsensor system 30. The SOC indicates a quantity or level of electricalenergy stored in the energy storage units 14, 16 and may be determinedby controller 64 using voltage and/or current measurements provided tocontroller 64 from sensor system 30. The SOH of the energy storage units14, 16 refers to the ability of the energy storage units 14, 16 to meetrated performance during discharge (e.g., supplying a load) or duringcharge. The SOH may be determined from a variety of parameters. Forexample, where the energy storage units 14, 16 include one or morebatteries, the SOH may be based on a battery terminal voltage as afunction of current, an estimate of internal battery resistance, abattery temperature, a battery voltage at a given value of the SOC,and/or trends of battery resistance over the life or calendar age of abattery.

At step 118, the power-split control technique 112 receivestime-variable desired vehicle performance data that reflects a real-timepower demand from the propulsion system 10. Such time-variable desiredvehicle performance data may be determined from a user input such as anacceleration or deceleration event, for example, or from informationattained from a predetermined vehicle route or duty cycle, such as frominformation stored on database 74.

At step 120 the impact of operating energy storage units 14, 16according to the power split is determined. Specifically, thetime-variable desired performance data, initial power split, andreal-time SOC and real-time SOH data is input to degradation models forthe energy storage units 14, 16 at step 120. The degradation models 120are used to determine a change in the state of health, ΔSOH, for eachenergy storage unit 14, 16 as well as a change in the state of charge,ΔSOC, for each energy storage unit 14, 16 based on the real-time SOC andSOH values 116 and the initial power split 114. At step 120, thedegradation models are also used to determine the maximum poweravailable from the first and second energy storage units 14, 16, whichdecreases over the life of the first and second energy storage units 14,16.

At step 122, power-split control technique 112 determines whetheroperating the energy storage system 12 in accordance with the initialpower split violates any system performance constraint functions. Thesesystem performance constraint functions may include functions thatdefine certain thresholds for the propulsion system, such as a thermallimit, maximum power, maximum current, and/or maximum voltage, asexamples.

If operation at the initial power split does violate a systemperformance constraint function 124, power-split control technique 112modifies the power split between the first and second energy storageunits 14, 16 at step 126 and then returns to step 120 to determine theimpact of the modified power split from the degradation models. Forexample, if the initial power split assigned 30 percent of the totalpower demand to first energy storage unit 14 and the remaining 70percent of the total power demand to second energy storage unit 16, thepower split may be modified at step 126 to assign 40 percent of thetotal power demand to first energy storage unit 14 and the remaining 60percent to second energy storage unit 16.

If, on the other hand, operation at the initial power split does notviolate a system performance constraint function 128, power-splitcontrol technique 112 proceeds either to step 129 to determine if thepower split is validated or proceeds directly to step 130 to run a powersplit algorithm, as described below.

In the event that the current power split was not determined as a resultof running a power split algorithm, such as during a propulsion systemstart up where the current power split is determined from a defaultvalue, power-split control technique 112 proceeds directly from step 122to step 130 to run a power-split algorithm that identifies an optimizedpower split or power allocation for the energy storage units 14, 16. Inthe exemplary embodiment described herein, the power-split algorithm isa multi-objective optimization algorithm that identifies an optimalvector of power split coefficients that provides an optimized tradeoffbetween the deterioration of the energy storage units 14, 16 and themaximization of the performance of the propulsion system 10, asdescribed in detail below. In alternative embodiments, the power splitalgorithm may be a simplified filter-based algorithm, a rule-based orlogic-based algorithm, or an algorithm based on one or more look-uptables.

According to various embodiments of the invention, the multi-objectiveoptimization algorithm interfaces with the nonlinear models that definethe energy storage system 12, such as, for example, models for theefficiency of the propulsion system power electronics and the overallefficiency of the power train of the propulsion system 10. Themulti-objective optimization algorithm manipulates the inputs of thenonlinear models, such as time variable performance requirement, devicecurrent and voltages, switching frequency, power factors, and the like,in order to achieve the desired model and system outputs, including adesired operating efficiency, fuel economy, and maximized power outputand minimized changes in the state of health (SOH) of the energy storageunits 14, 16 subject to the operational constraints of the propulsionsystem 10.

The multi-objective optimization algorithm incorporates differentmethods of optimization according to various embodiments. As onenon-limiting example, evolution algorithms that incorporate optimizationtechniques may be used to simulate natural evolutional processes. Suchevolution algorithms are robust to non-smooth, non-linear, andmulti-modal transfer function relationships. Alternatively,gradient-decent optimization techniques suitable for smooth anduni-modal transfer function relationships may be applied. As yet anotherexemplary embodiment, the optimization algorithm maybe simplified ashigh-low pass filter based, rule/logics based, or look-up table based toreduce computational demand and simplify real-time implementation.

In operation, the multi-objective optimization algorithm probes thevarious nonlinear models of the energy storage system 12 to identify aPareto-optimal set of input-output vector tuples that satisfy theoperational constraints of the energy storage system 12. Eachinput-output tuple corresponds to an input vector of power split ratios,and an output vector of metrics such as change in the state of health(SOH) of the energy storage units 14, 16 of the energy storage system12, change in the state of charge (SOC) of the energy storage units 14,16 of the energy storage system 12, and the available reserve peakperformance of the energy storage units 14, 16 of the energy storagesystem 12. The Pareto-optimal input-output tuples reside on the Paretoor efficient frontier of solutions, and are mutually and equally goodtradeoff solutions in the absence of further decision-makinginformation.

The multi-objective optimization algorithm uses a decision-makingfunction to perform an automated selection of a specific Paereto-optimalpower-split strategy to be deployed as a reference command that definesa power split for the energy storage units 14, 16. The decision-makingfunction is based on a heuristic model that is self adjusted orcorrected and that predicts the power and energy needs of the propulsionsystem 10 for a predetermined number of future time steps. Themulti-objective optimization algorithm superimposes the decision-makingfunction on the Pareto-optimal set of power split strategies to filterand identify an optimal power split strategy that optimizes the vehiclesystem's performance and health over the future time steps.

After running the multi-objective optimization algorithm at step 130,power-split control technique 112 begins an operating loop that testsand validates the power split output by the multi-objective optimizationalgorithm. As illustrated in FIG. 5, the power-split control technique112 returns to step 120 and determines the impact of the new power splitfrom the degradation models, in a similar manner as described above withrespect to the initial power split. Power-split control technique 112then proceeds to step 122 and determines whether operating according tothe new power split violates any system constraint functions.

If at step 122, power-split control technique 112 determines that thenew power split does violate a system constraint function 124, the powersplit is modified at step 126. According to one embodiment, power-splitcontrol technique 112 may modify the power split by an incrementalvalue, such as by decreasing the usage of one of the energy storage unitby a certain percentage and increasing the usage of the another energystorage unit to generate the remainder of the desired power output.Alternatively, power-split control technique 112 may rerun themulti-objective optimization algorithm to generate a new power split,this time applying different weights to the non-linear models.

If the new power split does not violate any system constraints 128,power-split control technique 112 proceeds to step 129 and determineswhether the current power split has been validated. During this step,the change in the state-of-health, ΔSOH, and change in thestate-of-charge, ΔSOC, resulting from the current power split areassessed to determine if the current power split will cause to great ofan impact on the state-of-health and/or state-of-charge of the energystorage system. In one embodiment, the change in the state-of-health,ΔSOH, and change in the state-of-charge, ΔSOC, may be compared torespective predefined thresholds.

If either of the change in the state-of-health, ΔSOH, and the change inthe state-of-charge, ΔSOC, exceeds a threshold, then the current powersplit has not been validated 131. In this situation, the power-splitcontrol technique 112 applies the multi-objective optimization algorithmagain at step 130 and the power-split control technique 112 continues toiteratively adjust the power split running through a loop definedbetween steps 120, 122, 129, and 130.

If, at the end of a predetermined number of iterations, power-splitcontrol technique 112 determines that the most recent iteration of thepower split derived from the multi-objective optimization algorithm doesnot violate the system constraint functions 128 and the power split hasbeen validated 133, power-split control technique 112 proceeds tooptional step 135 (shown in phantom) as described below.

In one embodiment, the multi-objective optimization algorithm may outputmultiple possible power splits at step 130 during a single iteration.For example, during a given iteration the multi-objective optimizationalgorithm may output a first power split stated to achieve ten years oflife for 85% of the customers and a second power split stated to achievenine years of life for 95% of the customers. Assuming each of thesemultiple power splits does not violate a system constraint function atstep 122 and has been validated at step 129, the power-split controltechnique 112 determines which of these power split strategies to employusing trade-off decision making at step 135. This trade-off decisionmaking may be an automated process based on predetermined weighting ofdifferent factors and or predetermined thresholds for those factors orbe determined based on a user selection. In an alternative embodiment,the trade-off decision making may be incorporated as part of themulti-ojbective optimization algorithm at step 130.

Following the trade-off decision making of step 135, power-split controltechnique 112 proceeds to step 134 and outputs a power allocation of theenergy storage units to the controller 64. The power allocationcorresponds to the most recent iteration of the power split andindicates how the total power demand is to be divided up between theenergy storage units. Controller 64 implements the power allocation viaappropriate control commands to first and second bi-directional DC-DCconverters 26, 28.

Power-split control technique 112 is periodically repeated duringreal-time operation of the propulsion system 10. According to variousembodiments, the frequency with which power-split control technique 112is used to define new power splits may be determined as a function oftime, changing operating conditions of the vehicle, a changing state ofthe energy storage system, or a combination thereof.

Optimized operation of a propulsion system for a hybrid or electricvehicle may also be achieved by dynamically regulating the voltage ofthe DC bus 36. While the dynamic regulation technique is described belowwith respect to propulsion system 10 of FIG. 1, it is contemplated thatthe technique may be extended to control the DC link voltage(s) ofalternative propulsion system configurations, such as, for example,propulsion system 78 (FIG. 2) or propulsion system 92 (FIG. 3). In oneembodiment, the dynamic DC bus voltage regulation is carried outsimultaneously with the above-described power-split control technique112. In yet another embodiment, the dynamic DC bus voltage regulationmay be carried-out independently without the above-described power splitcontrol technique 112.

Referring now to FIG. 6, and with continued reference to the elements ofFIG. 1 where appropriate, a dynamic voltage control technique 136 forregulating the DC bus voltage of propulsion system 10 is set forth. Inaddition to controlling the power split between the energy storage units14, 16 of energy storage system 12, controller 64 also dynamicallycontrols the DC link voltage of the DC bus 36 accordingly so thatpropulsion system 10 can approach its optimal efficiency duringoperation. As described in detail below, controller 64 monitors a DCvoltage of the DC bus 36 and computes an optimal voltage command foreach time step of operation and continually transmits the voltagecommands to the first and second bi-directional DC-DC converters 26, 28via control lines 66.

At step 138, the dynamic voltage control technique 136 determines thereal-time voltage of the DC bus either through a measurement receivedfrom voltage sensor 38 or by accessing the previous DC bus voltagecommand transmitted by controller 64 to first bi-directional DC-DCconverters 26, 28. This previous DC bus voltage command may be aninitial voltage command transmitted upon startup of the propulsionsystem 10 or the voltage command transmitted during a previous time stepduring real-time operation of propulsion system 10.

Dynamic voltage control technique 136 accesses the real-time torque andreal-time speed values of first and second electromechanical devices 46,50 at step 140. Using the real-time torque the real-time DC bus voltage,dynamic voltage control technique 136 identifies a correspondingscheduled speed at step 141.

According to one embodiment, the scheduled speed corresponding to thereal-time torque and real-time DC bus voltage is determined from avoltage scheduling look-up table indexed by measured torque of theelectromechanical device and DC bus voltage. In one embodiment, thevoltage scheduling look-up table is generated from a voltage schedulingmap, such as, for example, voltage scheduling map 144 illustrated inFIG. 7, which is a contour plot of the optimal voltage generated for amesh grid of torque and speed of the electromechanical device. As oneskilled in the art will recognize, FIG. 7 is shown for illustrationpurposes as a single quadrant, i.e., optimal voltage for positive torqueand positive speed. However, the contour plot used for control purposeswould include four quadrants, i.e., both positive and negative torqueand positive and negative speed. The voltage scheduling map definesoptimal DC bus voltages over a range of operating torques and operatingspeeds for a particular electromechanical device. As shown in FIG. 7,the voltage scheduling map 144 includes a number of operating curves146, 148, 150, 152, 154, 156 corresponding to different DC bus voltagelevels, such as, for example 250 V, 350 V, 450 V, 550 V, 650 V, and 700V, for operating a particular electromechanical device. Given a pair ofinputs of motor torque and speed, the voltage scheduling look-up tablegenerated from the voltage scheduling map 144 may be used to identify anoptimal DC voltage for the vehicle propulsion system under which thesystem loss is minimal. As one example, if the real-time DC bus voltageis 250 V and the real-time torque is 20 Nm, the scheduled speed would bedetermined to be 2000 rpm at step 141 based on the voltage schedulingmap 146.

At step 158, the real-time operating speed of the electromechanicaldevice is compared to the scheduled speed of the electromechanicaldevice as determined at step 141. Dynamic voltage control technique 136next determines whether the difference between the scheduled speed andthe real-time operating speed of the electromechanical device is greaterthan a threshold at step 160. If the difference between the scheduledspeed and real-time operating speed is greater than a threshold value162, a new voltage command is generated at step 163.

At step 163, dynamic voltage control technique 136 determines the newvoltage command value from a voltage scheduling look-up table generatedfrom the voltage scheduling map 144 and based on the real-time torqueand real-time speed values for the electromechanical device. Followingthe above-described example with a scheduled speed of 2000 RPM, torqueof 20 Nm, and DC bus voltage of 250 V, if the real-time speed hasincreased from 1500 RPM to 2500 RPM, dynamic voltage control technique136 will generate a new voltage command at step 163 to cause the DC busvoltage to shift up to a higher voltage level such as 350 V(corresponding to curve 148). If the real-time operating point of theelectromechanical device, as determined from the real-time torque andreal-time speed values, does not fall on one of the operating curves ofthe voltage scheduling map 144, the voltage command value may bedetermined by linear interpolation or by selecting the closest operatingcurve to the real-time operating point.

The new voltage command generated at step 163 is transmitted to thefirst and second bi-directional DC-DC converters 26, 28 at step 164thereby causing the voltage on the DC bus to shift either up or down inaccordance with the new voltage command. In the above-described example,the voltage on the DC bus is controlled to shift up and down by apredefined voltage interval, such as, for example, in 50 V or 100 Vsteps. However, alternative embodiments may generate voltage commandsthat shift the voltage of the DC bus in larger or smaller steps.

If, on the other hand, the difference between the scheduled speed andthe real-time operating speed of the electromechanical device is notgreater than the threshold value 166, dynamic voltage control technique136 returns to step 140 after initiating an optional wait step 168(shown in phantom).

In propulsion system embodiments that include multiple electromechanicaldevices, a separate voltage scheduling map is generated for eachelectromechanical device. In one embodiment, the voltage scheduling mapis empirically derived for each electromechanical device offline. Forpropulsion systems having multiple electromechanical devices coupled toindependent DC buses, such as the embodiments illustrated in FIGS. 2 and3, individual voltage commands are generated in the manner describedwith respect to steps 138-168 of dynamic voltage control technique 136and used to independently control the voltage on each DC bus.Alternatively, where the electromechanical devices are coupled to acommon DC bus, such as the embodiment illustrated in FIG. 1, voltagecommands are generated in the manner described with respect to steps138-168 of dynamic voltage control technique 136 and then fused togetherinto a voltage command to control the voltage on the DC bus.

In one embodiment, the individual voltage commands for eachelectromechanical device are combined using voting logic, which maydefine the fused voltage command as the median or mode of the voltagesfrom each of the individual voltage commands. In another embodiment, thefused voltage command is determined using weighting logic that weightseach of the individual voltage commands with a weighting number between0 and 1. The weighting number for each electromechanical device isselected as an index of how much the varying voltage impacts the overalloperating efficiency of the propulsion system. Weighting numbers may bedetermined based on one or more known operating parameters of theelectromechanical device, such as maximum power, maximum efficiency, andhigh efficiency range. In such an embodiment, electromechanical deviceswith high power output, low efficiency, and narrow efficiency rangeswill be given high index values or weighting numbers. Alternatively,weighting numbers may be determined dynamically based on real-timeoperating conditions of the electromechanical device. In this case, theweighting number for an electromechanical device would be determinedspecific to a particular voltage level and may vary with adjustments tothe scheduled voltage of the DC bus.

Dynamic DC link voltage control technique 136 includes logic to preventthe transmission of voltage commands that would cause undesirablefluctuations in the DC bus voltage during operation thereby makingdynamic control technique 136 robust to noise. To accomplish thisdynamic control technique 136 implements a new voltage command only whenthe change in the real-time speed of the electromechanical devicebetween consecutive iterations exceeds a predetermined threshold value.

Referring now to FIG. 8, a powertrain or propulsion power splittechnique 200 is set forth that optimizes the power split between thepower generating components of the propulsion system of a hybridelectric vehicle, which operate together to deliver a desired poweroutput to a final drive of the vehicle. Powertrain power split technique200 may be adapted to various propulsion system configurations,including systems having an electric-only powertrain with one or moremotors and hybrid systems in which the powertrain includes an internalcombustion engine (ICE) and an electric powertrain having one or moremotors, such as, for example, propulsion system 10 of FIG. 1 orpropulsion system 246 of FIG. 9. In the embodiment described below,power split technique 200 optimizes the overall system efficiency bysplitting the power demand between an ICE and the electric powertrainwhile meeting, maintaining, and sometimes exceeding desired performance.The desired power output is delivered to the final drive of thepropulsion system (i.e., transmission 56, optional gears 60, and thewheels/axle 58). While power split technique 200 is described below withrespect to propulsion system 246, one skilled in the art will recognizethat the concept disclosed herein may be extended to alternative hybridpropulsion systems.

Typically ICEs have a relatively low operating efficiency as compared toelectric motors. For example, the operating efficiency of an exemplaryICE may be approximately 30% or less, whereas the operating efficiencyof an electric powertrain having one or more motors may be in a range ofapproximately 80 or 90 percent or higher. Therefore, in optimizing theenergy efficiency of the propulsion system, powertrain power splittechnique 200 may be configured to operate with an assumption that theICE is the least efficient power producing component within thepowertrain in one embodiment of the invention. As described in detailbelow, in circumstances where the electric powertrain is capable ofproducing the current power demand for the propulsion system, powersplit technique 200 defines the power split such that propulsion systemoperates in an electric-only mode to maximize system efficiency. Insituations where the electric powertrain is not capable of meeting thedesired power demand, power split technique 200 defines a power splitbetween the ICE and electric powertrain that targets operating the ICEat its most efficient operating point.

As used herein, the phrase “least efficient power source” refers to thepower source within the powertrain that has the lowest operatingefficiency as compared to the other power sources within the powertrain,whether the powertrain is a hybrid powertrain comprised of an ICE andone or more motor/generator units or an all-electric powertraincomprised of one or more motor/generator units. While theabove-described embodiment assumes the ICE is the least efficient powerproducing component of a hybrid powertrain, in alternative embodiments,power split technique 200 may be configured to query one or moredatabases to determine the relative efficiency data for each of thepower producing components of the powertrain. Based on this query, powersplit technique 200 may be configured to maximize the operatingefficiency of the least efficient power-generating component of thepower train, whether that component is an ICE or motor/generator unit,in a similar manner as described above.

Power split technique 200 begins at block 202 by determining desiredvehicle performance data that reflects a real-time power from thepropulsion system 246 and determining operating parameters associatedwith the desired vehicle performance, such as, for example, power,torque, speed, and/or acceleration. Where drive cycle information isknown, such as in vehicles that follow predefined routes, this desiredperformance may be determined from a predefined speed versus timeprofile for the propulsion system, which may be used to derive operatingparameters related to torque or power demand for propulsion systemoperation. In situations where the desired upcoming performance is notknown, power split technique 200 may estimate desired performance basedon previous operating history or operate in a reactionary mode byestimating desired performance based on operator pedal inputs. Forexample, if power split technique 200 senses that the driver isaccelerating, power split technique 200 may estimate the desired torqueassociated with the acceleration and use the estimated torque todetermine the performance data for the propulsion system 246.

At block 204 power split technique 200 determines whether the electricpowertrain 247 alone, constituting motors 46, 50, is capable ofproducing an output that will meet the operating parameterscorresponding to the desired performance or if the ICE 62 must be usedto supplement the electric powertrain 247 in order to attain the desiredperformance. If the electric powertrain 247 is capable of producing thedesired performance alone 206, power split technique 200 defines thepower allocation for the ICE 62 to zero (i.e., turns the ICE 62 off),and proceeds to block 208 to define the power allocation within theelectric powertrain 247, as described in more detail below.

On the other hand, where the electric powertrain 247 is not capable ofproducing the desired performance on its own 210, power split technique200 accesses a database 212 that includes stored operating data for theparticular ICE 62, such as a specific fuel consumption (SFC) map for theengine or other engine efficiency map or an efficiency curve as afunction of operating conditions. In one embodiment, database 212 ispart of database 74 of propulsion system 10 (FIG. 1) or propulsionsystem 246 (FIG. 9).

Next, power split technique 200 identifies an optimum operating pointfor the ICE 62 at block 214 using the engine operating data storedwithin database 212. This optimum operating point corresponds to a pointwhere the ICE 62 is operating at a maximum efficiency. At block 216,power split technique 200 determines whether the actual power output ofthe ICE 62 when operating at the optimum operating point is greater thanor equal to the desired performance for the propulsion system 246, asdetermined at block 202. If not 218, power split technique 200 proceedsto block 208 wherein a power allocation for the electric powertrain 247is defined.

In an embodiment where the electric powertrain includes a single motoror electromechanical device, power split technique 200 allocates theremainder of the power output to the single motor. Where the electricpowertrain includes multiple motors or electromechanical devices, suchas propulsion system 246 of FIG. 9 on the other hand, power splittechnique 200 allocates the remainder of the power output amongst theindividual motors 46, 50 to achieve an optimum overall electricpowertrain efficiency that balances the performance of the individualmotors.

In one embodiment, the electric powertrain power allocation isdetermined using an optimization algorithm that operates based on motordata stored within database 212, which may be provided as part ofdatabase 74 of propulsion system 10 (FIG. 1) in one embodiment.According to various embodiments, database 212 may include predefinedefficiency contour maps for each of the motors within the electricpowertrain 247 as well as data relating to other operatingcharacteristics of the motors 46, 50, such as, for example, voltage,current, variable frequency (for an AC motor), inverter or driveefficiency.

In one embodiment, the optimization algorithm applied by power splittechnique 200 to determine the power split within the electricpowertrain 247 is one of a filter-based algorithm, a rule-basedalgorithm, a weighted or logic-based algorithm, or an algorithm based onefficiency maps or one or more look-up tables that contain data thatcorrelates power output and operating efficiency for each of the motors46, 50, associated inverters 44, 48, or a combination thereof (i.e.,overall operating efficiency of loads 40, 42). Where the algorithmoperates using data within one or more look-up tables, the look-up tabledata is then used to identify the relative efficiencies of each of themotors 46, 50 within the electric powertrain 247 and to maximize theoverall operating efficiency of the electric powertrain 247 bymaximizing the operating efficiency of the least efficient motor. Inembodiments where the algorithm is weighted or logic-based, theindividual motors 46, 50 may be assigned weights between zero and onebased on their relative efficiencies. For example, relatively lossy orinefficient motors may be assigned higher weights, whereas moreefficient motors may be assigned weights closer to zero.

As one non-limiting example of a look-up table based optimizationalgorithm, assume the electric powertrain contains two electric motors,M1 and M2, with M1 being less efficient than M2. The optimizationalgorithm first determines whether the power demand from the electricpowertrain exceeds the output capabilities of M2. If M2 is capable ofproducing the total power demand, the power output of M1 is set equal tozero and the power split for the electric powertrain is defined with M2producing the entire power output of the electric powertrain. If M2 isnot capable of producing the total power demand, on the other hand, theoptimization algorithm accesses data stored within an appropriatelook-up table to determine an operating point for M1 that corresponds tothe most efficient operating point for M1. The power split for theelectric powertrain is then defined with M1 producing a power outputcorresponding to the point of maximum efficiency and M2 operating toproduce any remaining power output to meet the current power demand. Inthe event that the power output of M1 exceeds the current power demandwhen M1 is operating at the maximum efficiency point, the power outputof M1 is scaled back to match the current power demand.

Alternatively, the optimization algorithm may be a multi-objectiveoptimization algorithm that determines an optimal vector of operatingcoefficients that maximizes the overall operating efficiency of theelectric powertrain. In such an embodiment, the multi-objectiveoptimization algorithm may take into account a number of predefinedfunctions that may include, as examples, a set of system constraints,operating costs, motor age and health data, and motor efficiency maps.In such an embodiment,

Referring back to decision block 216, in the event the output power ofthe ICE 62 is greater than the power demand when operating at themaximum efficiency point 220, power split technique 200 performs acomparison to determine whether the power output of the ICE 62 exceedsthe power demand of the propulsion system 246 at block 224. Where theICE 62 is not producing any excess power output 226 when operating atthe operating point defined at block 214, power split technique 200 setsthe power allocation of the electric powertrain 247 to zero at block 222and proceeds to output the current power split at block output powersplit 228, as described in more detail below.

On the other hand, if the power output of the ICE 62 does exceed thepower demand of the propulsion system 230, power split technique 200determines whether to use the excess output of the ICE 62 to charge oneor more of the energy storage devices 14, 16 provided within the energystorage system 12 at block 232. According to one embodiment, power splittechnique 200 determines whether to charge the energy storage system 12based on a current SOC and, optionally, a current SOH of the energystorage device(s) 14, 16 within the energy storage system 12. The SOHand SOC may be determined in a similar manner as described with respectto step 116 of power-split control technique 112 (FIG. 5). Using the SOCand SOH, power split technique 200 then accesses degradation modelsstored within database 212 for each energy storage device(s) 14, 16 ofthe energy storage system 12. If power split technique 200 determinesthat the energy storage system 12 is in need of a charge and applyingsuch a charge would not violate a system constraint 234, power splittechnique 200 allocates excess engine power among the motors (negativeor zero values) and generator at block 235 and uses the excess enginepower to charge the energy storage system 12 at block 236. In such asituation, a first subportion of the power output of the ICE 62corresponding to the desired power demand is supplied to the final drivecomponents (e.g., transmission 56, gears 60 and wheels/axel 58) of thepropulsion system 246 and a second subportion of the power output of theICE 62 or the excess engine power is supplied to energy storage system12.

The excess power generated by ICE 62 may be provided to energy storagesystem 12 through a contactor or switching device 268 coupled to the DCbus 36. Controller 64 may be programmed to close contactor 368 to chargeat least one of energy storage unit 14 and energy storage unit 16 wherepower split technique 200 determines that the energy storage system 12is in need of a charge and applying such a charge would not violate asystem constraint 234. In one embodiment, the excess power output of ICE62 may be allocated to one or both of energy storage units 14, 16 inaccordance with the reverse power split technique described with respectto FIG. 10.

If, on the other hand, power split technique 200 determines either thatthe energy storage system 12 does not need a charge or that charging theenergy storage system 12 using the available excess power output fromthe ICE 62 would violate a system constraint 238, power split technique200 modifies the operating point of the ICE 62 at block 240 such thatthe ICE 62 produces an output corresponding to the current power demand.

At block 228, power split technique 200 outputs a power split asdetermined by block 208, block 222, or block 240 to controller 64 of thepropulsion system 246, which applies appropriate controls to the ICE 62and/or motor(s) 46, 50 of the propulsion system 246. Following anoptional wait step, shown in phantom at block 242, power split technique200 returns to block 202 to begin a new iteration of the performancedata and power split determination for the hybrid powertrain.

While power split technique 200 is described above with respect to thepropulsion system of a hybrid electric vehicle, it is contemplated thatportions of technique 200, including the power allocation decisions madeat block 208, may be used in the context of an all electric vehicle.

Referring now to FIGS. 9 and 10, a reverse power split technique 244 isdisclosed that is useable to recharge one or more energy storage unitswithin an energy storage system, such as energy storage system 12 of apropulsion system 246. Similar to propulsion system 10 of FIG. 1,propulsion system 246 includes an energy storage system 12 having energystorage units 14 or 16. Other elements and components common topropulsion system 10 and propulsion system 246 are referred to hereinwith similar part numbering as appropriate.

As shown in FIG. 9, propulsion system 246 includes a rectifier 248coupled to a receptacle 250 having contacts 252, 254 configured to matewith a plug or connector 256 having contacts 258, 260 of a externalpower source 262. In the embodiment shown, rectifier 248 is coupled toDC-DC converters 26, 28, however, one skilled in the art will recognizethat rectifier 248 could be positioned in alternative locations ofpropulsion system 246 to provide charging power to energy storage system12. While rectifier 248 is illustrated in FIG. 9 as being mountedon-board propulsion system 246, one skilled in the art will recognizethat rectifier 248 may be mounted off-board propulsion system 246 andintegrated within external power source 262 in an alternativeembodiment. As an alternative to the plug-in charging configurationshown in FIG. 9, energy storage system 12 of propulsion system 246 maybe configured to accept charge wirelessly via an inductive charger.

In one embodiment, it is contemplated that external power source 262 isan AC source and that one, two, or three phases of external power source262 may be used to provide 120 V or 240 V of AC power. In aconfiguration designed for operation from a three phase AC externalpower source 262, rectifier 248 may be modified to include twoadditional diodes (not shown) for the third phase of a three-phaserectifier. In an alternative embodiment where external power source 262is a DC source, rectifier 248 helps to ensure that the charging voltagetransferred to DC bus 36 has the correct polarity.

As shown in FIG. 9, a contactor or switching device 265 is provided toselectively couple the output of rectifier 248 to DC bus 36. Controller64 is coupled to contactor 265 via control lines 269 and is programmedto operate contactor 265 in an open position, wherein the power outputof external power source 262 is decoupled from DC bus 36 and a closedposition, wherein the power output of external power source 262 iscoupled to DC bus 36.

In hybrid embodiments where propulsion system 246 includes optional ICE62, an optional charging assembly 264 (shown in phantom) including analternator 299 or generator, a rectifier 266, and a contactor 268 orswitch are coupled to the DC bus 36 as shown in FIG. 9. According tovarious embodiments, contactor 268 may be constructed as anelectromechanical switching device or a solid-state type switchingdevice. Controller 64 is electrically coupled to contactor 268 viacontrol lines 270 and configured to selectively operate contactor 268 inan open position, wherein an output of ICE 62 is decoupled from DC bus36 and a closed position, wherein an output of ICE 62 is coupled to DCbus 36. It is contemplated that one or more additional contactors may beprovided within propulsion system 246 controlled by controller 64 toselectively transfer charging power from external power source 262, ICE62, or motors 48, 50 via regenerative braking to one or both of energystorage units 18, 20.

Referring now to FIG. 10, and with continued reference to the elementsof propulsion system 246 of FIG. 9 where appropriate, the details of acharging power split technique or reverse power split technique 244 willbe described. While reverse power split technique 244 is describedherein with respect to the elements of propulsion system 246, it iscontemplated that reverse power split technique 244 may be adapted foralternative propulsion system configurations, including electric onlysystems having one or more energy storage units, hybrid systemsincluding an internal combustion engine (ICE) and a single energystorage unit or two or more energy storage units, as well as thepropulsion system configurations illustrated in FIGS. 1-3.

Reverse power split technique 244 begins at block 272 by accessing datafor the energy storage system 12. This data may include identifyinginformation for energy storage units 14, 16 such as battery type, forexample, as well as a real-time state of charge (SOC) and real-timestate of health (SOH) data of energy storage units 14, 16. SOC and SOHdata may be determined from information received from energy storageunit sensor system 30 at periodic intervals during operation ofpropulsion system 10. As non-limiting examples, the SOH data mayrepresent a battery terminal voltage as a function of current, anestimate of internal battery resistance, an estimate of battery capacity(Ah), a battery temperature, a battery voltage at a given value of theSOC, and/or trends of battery resistance over the life or calendar ageof a battery.

The parameters of the charging power are identified at block 274.Namely, reverse power split technique 244 detects the presence of excesspower that is available to charge energy storage system 12 anddetermines the characteristics of that excess power. This excess powermay be available where propulsion system 246 is operating in any of thefollowing modes: a regenerative braking mode, a motoring mode where theICE 62 is producing excess power usable to charge the energy storagesystem 12, and a charging mode where the vehicle is coupled to externalpower source 262. In any of these operating modes, reverse power splittechnique 244 is configured to assess the parameters of the excess powercurrently available for charging from the given charging source, whichmay be the ICE 62, one or more of electromechanical devices 46, 50, oran external or off-board power source 262 depending on the givenoperating mode.

Where propulsion system 246 is coupled to external power source 262, forexample, reverse power split technique 244 determines the parameters ofthe charging power available from the external power source 262, suchas, for example, the power and energy (kW, kWh) that external powersource 262 is capable of supplying. In various embodiments, receptacle250 and/or connector 256 may be configured to send signals to controller64 indicative of the charging parameters of external power source 262.In any of these operating scenarios, reverse power split technique 244may be configured to access stored operational use data and/or knownduty cycles to estimate a duration that the excess charging power willbe available.

After the parameters of the charging power are identified at block 274,reverse power split technique 244 defines an initial charging powerallocation at block 276. This charging power allocation apportions agiven percentage of the available charging power to each of the energystorage units 14, 16 within the energy storage system 12. Depending onthe determined parameters of the available charging power and thecharacteristics of energy storage units 14, 16, the percentage ofcharging power allocated to each of the energy storage units 14, 16 maybe anywhere in the range of 0 to 100% of the total available chargingpower. As one example, this initial charging power allocation may evenlysplit the available charging power between energy storage units 14, 16as an initial default allocation. As another example, where energystorage unit 14 is a power battery and energy storage unit 16 is anenergy battery, the default initial charging allocation may supply allof the available charging power to the power battery in situations wherethe charging power will only be available for a short duration, such asduring a regenerative braking mode for example, since the power batteryis able to accept charge at a faster rate than the energy battery.

At block 278 the impact of the initial charging power allocation onenergy storage units 14, 16 is determined by inputting the initialcharging power allocation, real-time SOC data, and real-time SOH datainto degradation models specific to each of the energy storage units 14,16. Since energy storage units respond differently when charging anddischarging, the degradation models used at block 278 differ from thedegradation models 106 described with respect to FIG. 4. According tovarious embodiments, these charge-specific degradation models may takeinto account any combination of the following information for energystorage units 14, 16: charge cell or battery voltage, charge C-rate, aninternal resistance (rise) model, a capacity (loss) model as a functionof temperature, current, voltage, and/or a cumulative number of chargecycles. The charge-specific degradation models are used at block 278 todetermine a change in the state of health, ΔSOH, and the resultingchange in the state of charge, ΔSOC, for each energy storage unit 14, 16being charged in accordance with the initial charging power allocation.

At block 280, reverse power split technique 244 uses the output of block278 to determine whether charging energy storage system 12 violates anyenergy storage system constraints when being charged in accordance withthe initial charging power allocation. These energy storage systemconstraints may include functions that define certain thresholds for theenergy storage system, such as a thermal limit, maximum power, maximumcurrent, and/or maximum voltage of energy storage units 14, 16, asexamples.

If charging in accordance with the initial charging power allocationviolates an energy storage system constraint 282, reverse power splittechnique 244 modifies the charging power allocation at block 284 andthen returns to block 278 to determine the impact of the modifiedcharging power allocation on energy storage units 14, 16 from thedegradation models. In one embodiment, the modification may compriseadjusting the charging power allocation by a predefined step value, suchas, for example, five or ten percent.

If charging the energy storage system 12 in accordance with the initialcharging power allocation does not violate an energy storage systemconstraint 286, reverse power split technique 244 proceeds to block 288to determine whether the charging power allocation has been validated.Reverse power split technique 244 validates the charging powerallocation by running a charging power algorithm at block 290. Thus, thefirst step in determining if the allocation is validated at block 280 isto check if a charging power algorithm has been applied to the currentcharging power allocation.

If the charging power algorithm has not been applied to the currentcharging power allocation, reverse power split technique 244 determinesthat the allocation has not been validated 292 and proceeds to block 290to run the charging power algorithm. The charging power algorithm isconfigured to identify an optimal vector of charging power splitcoefficients that distributes the available charging power in a mannerthat optimizes the resulting SOC of the energy storage units 14, 16following the charging event while minimizing the deterioriation of theSOH as a result of the charge. In one embodiment, the charging poweralgorithm is a multi-objective optimization algorithm, similar to thepower-split algorithm described with respect to the dynamic power-splitcontrol technique 112 of FIG. 5, which identifies an optimized split ofthe available charging power to the energy storage units 14, 16 of theenergy storage system 12. In alternative embodiments, the charging poweralgorithm may be a simplified filter-based algorithm, a rule-basedalgorithm, a logic-based algorithm, or an algorithm operable based onone or more look-up tables.

Where the charging power algorithm is a multi-objective optimizationalgorithm, the charging power algorithm interfaces with the nonlinearmodels that define the energy storage system 12, including, for example,models of the efficiencies of the DC-DC converters 26, 28 coupled to therespective energy storage units 14, 16, other power electronic devicesprovided within propulsion system 10 (e.g., DC-AC inverters 44,48),dynamic thermal and/or mechanical models for the energy storage units14, 16, as well as energy storage degradation models for charging energystorage units 14, 16. The multi-objective optimzation algorithm may alsotake into account an expected usage of the energy storage units 14, 16based on predetermined drive cycles or past usage history stored ondatabase 74. The multi-objective charging power algorithm manipulatesthe inputs of the nonlinear models, such as the operating current andvoltages of power electronic devices, switching frequency, powerfactors, and the like, in order to achieve an optimized increase in theSOC of the energy storage units 14, 16 with a minimal change in thestate of health (SOH) of the energy storage units 14, 16 subject to theoperational constraints of the propulsion system 10. The multi-objectivecharging power algorithm may also be configured to define an optimizedcharging allocation that prioritizes charing of one of energy storageunits 14, 16 based on the expected upcoming usage of the propulsionsystem 246.

The multi-objective charging power algorithm incorporates differentmethods of optimization according to various embodiments. As onenon-limiting example, evolution algorithms that incorporate optimizationtechniques may be used to simulate natural evolutional processes. Suchevolution algorithms are robust to non-smooth, non-linear, andmulti-modal transfer function relationships. Alternatively,gradient-decent optimization techniques suitable for smooth anduni-modal transfer function relationships may be applied. As yet anotherexemplary embodiment, the optimization algorithm maybe simplified ashigh-low pass filter based, rule/logics based, or look-up table based toreduce computational demand and simplify real-time implementation.

In operation, the multi-objective charging power algorithm probes thevarious nonlinear models of the energy storage system 12 to identify aPareto-optimal set of input-output vector tuples that satisfy theoperational constraints of the energy storage system 12. Eachinput-output tuple corresponds to an input vector of charging powersplit ratios, and an output vector of metrics such as change in thestate of health (SOH) of the energy storage units 14, 16 of the energystorage system 12, change in the state of charge (SOC) of the energystorage units 14, 16 of the energy storage system 12. The Pareto-optimalinput-output tuples reside on the Pareto or efficient frontier ofsolutions, and are mutually and equally good tradeoff solutions in theabsence of further decision-making information.

The multi-objective charging power algorithm uses a decision-makingfunction to perform an automated selection of a specific Paereto-optimalcharging power split strategy to be deployed as a reference command thatdefines a charging power split for the energy storage units 14, 16. Thedecision-making function is based on a heuristic model that is selfadjusted or corrected and that predicts the charging power availablefrom the propulsion system 10 for a predetermined number of future timesteps. The multi-objective optimization algorithm superimposes thedecision-making function on the Pareto-optimal set of charging powersplit strategies to filter and identify an optimal charging power splitstrategy that optimizes the performance and health of the energy storagesystem 12 over the future time steps.

The charging power algorithm outputs a modified charging powerallocation to block 278 where the impact of the modified charging powerallocation is determined. Reverse power split technique 244 continues toiteratively adjust the charging power allocation through blocks 280,284, 288, 290 in the manner described above until, reverse power splittechnique 244 determines that the current charge split allocation hasbeen validated 294 following block 288. At this point, reverse powersplit technique 244 proceeds to charge one or more energy storage units14, 16 of the energy storage system 12 in accordance with the currentcharge split allocation at block 296.

As described above, embodiments of the invention utilize offline andonline optimization techniques for designing and operating vehiclepropulsion systems for electric vehicles and hybrid electric vehicles.The offline optimization technique determines a design configuration foran energy storage system of a vehicle propulsion system that minimizessize of the energy storage units within the energy storage system whileproviding a design configuration that achieves desired systemconstraints, such as maximum power output and desired years of life. Tofurther maximize the life span of the energy storage units providedwithin a given energy storage system, an online optimization techniqueis described herein that adjusts a power split between the energystorage units during operation of the vehicle propulsion system toachieve a total power demand of the propulsion system while monitoringthe state of charge and state of health of the energy storage units.Embodiments of the invention also utilize an online voltage regulationtechnique that dynamically controls the voltage of the DC bus based onthe speed of the electromechanical devices and a predetermined voltagescheduling map specific to each electromechanical device.

Embodiments of the invention also optimize power generation from thepropulsion system using an optimization technique that determines anoptimal power split between the power sources provided within thepropulsion system. This optimization technique aims to operate the leastefficient power source at its highest operating efficiency and uses oneor more additional power sources to generate any additional power demandas needed. Where the least efficient power source is producing morepower output than the current power demand, any excess power generatedmay be used to recharge one or more energy storage units provided withinthe propulsion system.

Embodiments of the invention further utilize an optimization techniquefor recharging an energy storage system using charging power generatedby regenerative braking, an ICE, or an external power source. Thisoptimization technique maximizes the life span of the individual energystorage units of the energy storage system while also maximizing thestate of charge of the energy storage units using degradation modelsthat assess the impact of recharging each of the energy storage unitswith the currently available excess power.

As described above, these online and offline techniques improve theoverall system performance and efficiency while optimizing the lifespanof the energy storage units and reducing the overall manufacturing costof the vehicle propulsion system.

One skilled in the art will appreciate that controller 64 may beimplemented via a plurality of components such as one or more ofelectronic components, hardware components, and/or computer softwarecomponents. These components may include one or more tangible computerreadable storage media that generally stores instructions such assoftware, firmware and/or assembly language for performing one or moreportions of one or more implementations or embodiments. Examples of atangible computer readable storage medium include a recordable datastorage medium and/or mass storage device. Such tangible computerreadable storage medium may employ, for example, one or more of amagnetic, electrical, optical, biological, and/or atomic data storagemedium. Further, such media may take the form of, for example, floppydisks, magnetic tapes, CD-ROMs, DVD-ROMs, hard disk drives, and/orelectronic memory. Other forms of tangible computer readable storagemedia not listed may be employed with embodiments of the invention.

A number of such components can be combined or divided in animplementation of the systems described herein. Further, such componentsmay include a set and/or series of computer instructions written in orimplemented with any of a number of programming languages, as will beappreciated by those skilled in the art.

A technical contribution for the disclosed apparatus is that it providesfor a controller implemented technique for controlling charging of oneor more energy storage devices in a manner that optimizes at least oneof a state of charge (SOC) and a state of health (SOH) of the energystorage device(s).

According to one embodiment of the invention, a charging system for avehicle includes a first energy storage device, a first DC-DC convertercoupled between a DC bus and the first energy storage device, and acontroller. The controller is programmed to identify charging parametersof a charging source coupleable to the first energy storage devicethrough the first DC-DC converter, apply an optimization algorithm toiteratively define a charging power allocation to charge the firstenergy storage device using the charging source, and selectively controlthe first DC-DC converter to recharge the first energy storage device inaccordance with the charging power allocation. The charging powerallocation optimizes at least one of a state of charge (SOC) and a stateof health (SOH) of the first energy storage device.

In accordance with another embodiment of the invention, a method ofcharging an energy storage system of a vehicle includes identifyingoperating parameters a plurality of energy storage units of the energystorage system, identifying a charging source available to recharge theplurality of energy storage units, and defining a charging powerallocation to recharge the plurality of energy storage units using thecharging source. The method also includes iteratively adjusting thecharging power allocation to optimize at least one of a state of healthand a state of charge of the plurality of energy storage units, andrecharging at least one energy storage unit of the energy storage systemin accordance with the adjusted charging power allocation.

In accordance with yet another embodiment of the invention, a vehiclepropulsion system includes a first energy storage unit coupled to a DCbus via a DC-DC converter, a switching device operable to couple acharging source to the DC bus, and a controller electrically coupled tothe switching device and the DC-DC converter. The controller isprogrammed to query parameters of a charging power available from thecharging source, access a state of charge (SOC) of the first energystorage unit and define a charging power allocation to recharge thefirst energy storage device with the charging power. The controller isfurther programmed to apply a multi-objective optimization algorithm toiteratively adjust the charging power allocation based on the parametersof the charging power and the SOC of the first energy storage unit andrecharge the first energy storage unit in accordance with the adjustedcharging power allocation.

While the invention has been described in detail in connection with onlya limited number of embodiments, it should be readily understood thatthe invention is not limited to such disclosed embodiments. Rather, theinvention can be modified to incorporate any number of variations,alterations, substitutions or equivalent arrangements not heretoforedescribed, but which are commensurate with the spirit and scope of theinvention. Additionally, while various embodiments of the invention havebeen described, it is to be understood that aspects of the invention mayinclude only some of the described embodiments. Accordingly, theinvention is not to be seen as limited by the foregoing description, butis only limited by the scope of the appended claims.

What is claimed is:
 1. A charging system for a vehicle comprising: afirst energy storage device; a first DC-DC converter coupled between aDC bus and the first energy storage device; and a controller programmedto: identify charging parameters of a charging source coupleable to thefirst energy storage device through the first DC-DC converter; apply anoptimization algorithm to iteratively define a charging power allocationto charge the first energy storage device using the charging source; andselectively control the first DC-DC converter to recharge the firstenergy storage device in accordance with the charging power allocation;and wherein the charging power allocation optimizes at least one of astate of charge (SOC) and a state of health (SOH) of the first energystorage device.
 2. The charging system of claim 1 wherein the chargingsource comprises an internal combustion engine (ICE); and wherein thecharging system further comprises a contactor operable in a closedposition to couple an output of the ICE to the DC bus via an alternatorand an open position to decouple the output of the ICE from the DC bus.3. The charging system of claim 2 wherein the controller is furtherprogrammed to: detect an excess power output from the ICE; and upondetection of the excess power output, cause the contactor to operate inthe closed position to permit a transfer of charging power from the ICEto the first energy storage device.
 4. The charging system of claim 1wherein the charging source comprises a power source located off-boardthe vehicle; and wherein the charging system further comprises acharging interface constructed to couple a power output of the chargingsource to the DC bus.
 5. The charging system of claim 1 wherein thecontroller is further programmed to: access a charging degradation modelfor the first energy storage device to determine an impact of chargingthe first energy storage device according to an initial charging powerallocation; and modify the initial charging power allocation if theimpact exceeds an operating threshold of the first energy storagedevice.
 6. The charging system of claim 5 wherein the operatingthreshold comprises at least one of a thermal limit, a maximum power, amaximum current, and a maximum voltage of the first energy storagedevice.
 7. The charging system of claim 1 further comprising: a secondenergy storage device having a charging rate faster than a charging rateof the first energy storage device; and wherein the controller isfurther programmed to: identify an expected duration of availability ofthe charging source; and define the charging allocation based on theexpected duration of availability of the charging source and the ratesof charge of the first and second energy storage devices.
 8. Thecharging system of claim 1 further comprising: a second energy storagedevice; and wherein the controller is further programmed to: access anexpected usage for the first and second energy storage devices; andprioritize charging of one of the first energy storage device and thesecond energy storage device based on the expected usage.
 9. A method ofcharging an energy storage system of a vehicle comprising: identifyingoperating parameters a plurality of energy storage units of the energystorage system; identifying a charging source available to recharge theplurality of energy storage units; defining a charging power allocationto recharge the plurality of energy storage units using the chargingsource; iteratively adjusting the charging power allocation to optimizeat least one of a state of health and a state of charge of the pluralityof energy storage units; and recharging at least one energy storage unitof the energy storage system in accordance with the adjusted chargingpower allocation.
 10. The method of claim 9 further comprising applyingmulti-objective optimization algorithm to iteratively adjust thecharging power allocation.
 11. The method of claim 9 further comprisinga first portion of charging power available from the charging source toa first energy storage unit of the energy storage system and a secondportion of the charging power available from the charging source to asecond energy storage unit of the energy storage system.
 12. The methodof claim 11 further comprising: identifying a first rate with which thefirst energy storage unit is able to accept charging power from thecharging source; identifying a second rate with which the second energystorage unit is able to accept charging power from the charging source;comparing the first rate to the second rate; and prioritizing charge toone of the first energy storage unit and the second energy storage unitbased on the comparison.
 13. The method of claim 9 further comprisingiteratively adjusting the charging power allocation based on chargedegradation models of the plurality of energy storage units.
 14. Themethod of claim 9 further comprising: identifying the charging source asan internal combustion engine (ICE) provided within the vehicle; andclosing a contactor to transfer power generated by the ICE to at leastone energy storage unit of the energy storage system.
 15. A vehiclepropulsion system comprising: a first energy storage unit coupled to aDC bus via a DC-DC converter; a switching device operable to couple acharging source to the DC bus; and a controller electrically coupled tothe switching device and the DC-DC converter, the controller programmedto: query parameters of a charging power available from the chargingsource; access a state of charge (SOC) of the first energy storage unit;define a charging power allocation to recharge the first energy storagedevice with the charging power; apply a multi-objective optimizationalgorithm to iteratively adjust the charging power allocation based onthe parameters of the charging power and the SOC of the first energystorage unit; and recharge the first energy storage unit in accordancewith the adjusted charging power allocation.
 16. The vehicle propulsionsystem of claim 15 wherein the controller is further programmed toiteratively adjust the charging power allocation based on a chargingdegradation model of the first energy storage unit.
 17. The vehiclepropulsion system of claim 15 wherein the charging source comprises aninternal combustion engine (ICE) provided within the vehicle propulsionsystem.
 18. The vehicle propulsion system of claim 15 further comprisinga charging receptacle coupled to the DC bus; and wherein the chargingsource comprises an external power source coupleable to the DC busthrough the charging receptacle.
 19. The vehicle propulsion system ofclaim 15 further comprising a second energy storage unit; and whereinthe controller is further programmed to define the charging powerallocation to recharge the first energy storage device with a firstportion of the charging power and to recharge the second energy storagedevice with a second portion of the charging power.
 20. The vehiclepropulsion system of claim 19 wherein the controller is furtherprogrammed to iteratively adjust the charging power allocation based ona battery type of the first and second energy storage units, the batterytype comprising one of a power battery and an energy battery.